How this tool works

OCR PDF to Text: a practical guide

Renders the document and runs Tesseract locally, then downloads the recognized text as a UTF-8 TXT file with page labels. Language data and OCR libraries are hosted with the site.

Steps to use this tool

Select a scanned PDF and its OCR language.
Run OCR PDF to Text while local models load.
Download the TXT and proofread it against the scan.

Tested example — 19 October 2026

The Hindi model recognizes text from a rendered Devanagari scan; the exact returned excerpt is shown below.

Selected sample: hindi-scan.pdf (7720 bytes, 1 pages).

Measured output: hindi-scan-ocr.txt — 36 bytes.

Actual output excerpt:

Page 1
भारत हिंदी

Sample settings:

{
  "language": "hin"
}

Test environment: Node + native canvas + actual site-ui.js form integration in LinkeDOM Representative sample; inspect your own output.

Check the result

Read the recognized words beside the scan, especially names and amounts. Hindi matras and similar-looking digits need manual checking even after a successful run.

Files and privacy

The public tool processes selected documents in your browser. It does not send document bytes to a conversion server. The page and its bundled libraries still download from this website. Keep the original, use an up-to-date browser and inspect your output before sharing it. See the privacy policy for hosting and support information.

If processing fails

The OCR models and worker must finish downloading before recognition can run. Retry a smaller, clearer scan if phone memory or poor image quality prevents a result.

Implementation notes and sample evidence updated 2026-10-19. These notes describe the supported operation and its limits.

Check the local-processing claim in your browser’s Network panel.

OCR PDF to Text